Score the HiTOP-SR Instrument

Create a data frame with scores on all the HiTOP-SR scales.

Usage

score_hitopsr(
  data,
  items,
  srange = c(1, 4),
  prefix = "hsr_",
  missing = c("available", "complete"),
  calc_se = FALSE,
  append = TRUE,
  subset = NULL
)

Arguments

data

A data frame containing the HiTOP-SR items (numerically coded): all 405 of them, or, when subset is supplied, that short form's items.

items

A vector of column names (as strings) or numbers (as integers) corresponding to the HiTOP-SR items held in data — all 405, or, when subset is supplied, that short form's items. Items must be supplied in instrument order; a misordered mapping silently scores the wrong items, so a warning is issued when the names share a common prefix and trailing number but those numbers are not ascending. Duplicated entries are an error.

srange

An optional numeric vector specifying the minimum and maximum values of the HiTOP-SR items, used for reverse-coding. (default = c(1, 4))

prefix

An optional string to add before each scale column name. If no prefix is desired, set to an empty string "". (default = "hsr_")

missing

A string selecting how missing item responses are handled when computing scale scores. "available" (the default) averages whatever items are present (rowMeans(na.rm = TRUE)); "complete" returns NA for any scale with a missing item (rowMeans(na.rm = FALSE)). (default = "available")

calc_se

An optional logical indicating whether to calculate the standard error of each scale score. (default = FALSE)

append

An optional logical indicating whether the new columns should be added to the end of the data input. (default = TRUE)

subset

An optional hitop_subset object, as returned by hitop_subset(), describing a short form of the instrument. When supplied, data and items hold only that subset's item columns — in ascending instrument order, as the generate_*_hitopsr() forms lay them out — and only that subset's scales are scored. When NULL, all 405 items are expected and all 76 scales are scored. (default = NULL)

Value

A tibble containing all scale scores and standard errors (if requested) and all original data columns (if requested).

Details

For per-scale reliability estimates (Cronbach's alpha, McDonald's omega), use reliability_hitopsr().

Examples

# Score all HiTOP-SR scales from the simulated data
score_hitopsr(sim_hitopsr, items = 1:405, append = FALSE)
#> # A tibble: 100 × 76
#>    hsr_agoraphobia hsr_antisocialBehavior hsr_appetiteLoss hsr_bingeEating
#>              <dbl>                  <dbl>            <dbl>           <dbl>
#>  1             2.8                   2.75             2.67            2.67
#>  2             2.6                   2.75             3               2.33
#>  3             2.4                   2.75             2.67            2.33
#>  4             2.4                   2.38             2               2.67
#>  5             2.6                   2.5              2               2.67
#>  6             2.4                   3.12             2.67            2.33
#>  7             2.6                   2.38             2.33            1.33
#>  8             3                     2.38             2.67            1.67
#>  9             2.4                   2.38             1.67            2.33
#> 10             2.4                   2                2.33            1.67
#> # ℹ 90 more rows
#> # ℹ 72 more variables: hsr_bodilyDistress <dbl>, hsr_bodyDissatisfaction <dbl>,
#> #   hsr_bodyFocus <dbl>, hsr_callousness <dbl>, hsr_checking <dbl>,
#> #   hsr_cleaning <dbl>, hsr_cognitiveProblems <dbl>,
#> #   hsr_conversionSymptoms <dbl>, hsr_counting <dbl>,
#> #   hsr_dietaryRestraint <dbl>, hsr_difficultiesReachingOrgasm <dbl>,
#> #   hsr_diseaseConviction <dbl>, hsr_dishonesty <dbl>, …

# Score data collected with a two-scale short form. Select the item columns
# by name: `s$items` holds original HiTOP-SR numbers, which are column
# positions only in a data frame that is exactly the 405 items in order.
s <- hitop_subset("hitopsr", scales = c("Agoraphobia", "Appetite Loss"))
short <- sim_hitopsr[paste0("hsr_", s$items)]
score_hitopsr(short, items = names(short), subset = s, append = FALSE)
#> # A tibble: 100 × 2
#>    hsr_agoraphobia hsr_appetiteLoss
#>              <dbl>            <dbl>
#>  1             2.8             2.67
#>  2             2.6             3   
#>  3             2.4             2.67
#>  4             2.4             2   
#>  5             2.6             2   
#>  6             2.4             2.67
#>  7             2.6             2.33
#>  8             3               2.67
#>  9             2.4             1.67
#> 10             2.4             2.33
#> # ℹ 90 more rows